Abstract:With the deepening of power system reform, the implementation of energy conservation and emission reduction policies, the increase of wind power integration capacity and the application of new energy storage technology, the power system dispatch faces new challenges. Under the background, an environmental economic dispatch (EED) model is proposed for the wind-thermal-storage integrated system with direct power purchase from large consumers. A multi-objective optimization problem including the wind power output, carbon emissions trading, energy storage system and direct power purchase of large consumers is considered comprehensively in the model. Meanwhile, the influences of energy storage systems and large consumers on the environmental and economic benefits of wind-thermal combined system scheduling are analyzed. Besides, a chaotic adaptive glowworm swarm optimization (GSO) algorithm is introduced to solve the problem of oscillation in the optimization of traditional GSO algorithm. At the end, The IEEE-39 system is included for the simulation. It is shown that the proposed EED model is accurate, and the chaos adaptive glowworm swarm optimization algorithm is effective in solving this problem.

Abstract:Compared with electricity, hydrogen is easier to store and can play an important role in the high renewable energy integration. Under the background, this paper focuses on the influence of hydrogen demand (flexible hydrogen demand) at different time scales on the optimization of regional integrated energy systems. Firstly, the uncertainty of renewable energy output, demand-side response and flexible hydrogen demand are considered in the modeling of regional integrated energy systems. Then, the impact of hydrogen demand on the optimal dispatch of regional integrated energy systems is studied for different time scales with different photovoltaic penetration levels based on the hourly annual electricity load demand and photovoltaic output data. Finally, a simulation is included for verification with the goal of minimizing the annual operating cost of the system. It is shown that the system economy gradually improves as the time scale of hydrogen demand increases (the storage capacity of the terminal gradually increases) especially for area of the equipment operation, transaction with the upper-level grid, and demand-side response.

Abstract:Aiming at improving the renewable energy consumption level in the multi-energy system and quantify the influence of uncertain unit output on system scheduling, a multi-energy system containing hydrogen and gas energy storage is constructed and the operation characteristics of hybrid energy storage in the system are analyzed in this paper. Then, a multi-objective optimal scheduling model for multi-energy systems is proposed, and the uncertainty risk of wind turbines is described by the multi-objective conditional value at risk method. In addition, the fuzzy C-mean-comprehensive quality assessment and improved particle swarm optimization are utilized to transform the system uncertainty problem into a deterministic problem. Finally, the single-objective optimization results without uncertainty and the comprehensive objective optimization results with uncertainty are solved respectively. It is shown that (1) hybrid energy storage devices can effectively improve the consumption level of renewable energy and realize the multi-stage energy conversion. (2) the uncertainty of renewable energy increases the comprehensive cost of a multi-energy system. (3) the improved risk tolerance of system can improve scheduling results.

Abstract:In the future, the airport power supply system will incorporate a variety of distributed power sources and gradually develop towards the airport microgrid. In order to improve the operating economy of the airport microgrid, the airport microgrid needs a more effective dispatching strategy. Under the background, an improved sparrow search algorithm is proposed to improve the speed and accuracy of the traditional dispatching strategy. Firstly, the typical airport microgrid is considered as the research object and an optimized dispatching model for the airport microgrid is established. Then, the improved sparrow search algorithm is proposed which adds a non-linear change weight factor to prevent the algorithm from entering local convergence. At the end, the proposed algorithm is employed to solve the optimal dispatching of airport microgrid and it is compared with the basic sparrow search algorithm. The comparative analysis results show that the proposed algorithm has the advantages of fast convergence and high optimization accuracy, which can effectively reduce the operating cost of airport microgrid.

Abstract:With the wide application of microgrids in island area, the reliability evaluation of microgrid system becomes more complex and difficult. Firstly, k-means clustering algorithm is utilized for collecting typical scenes of microgrid operation with big data, and the "supply-load" characteristic which reflects the time correlation is used as the key feature. Secondly, a scenario probability distribution based Latin hypercube sampling method is proposed to ensure that the sampling frequency is identical to the scenario occurrence probability. Finally, according to the random sampling from the state time series of each component under different scenarios, the synthesis reliability index of each scenario can be computed by using the full probability formula. A microgrid benchmark is used to validate the effectiveness and accuracy of the proposed method. The results show that the proposed method proposed can quickly and correctly evaluate the reliability of the microgrid.

Abstract:With the increasingly high penetration of renewable energy into the power system, the inertia level of the power system is gradually decreasing, and the frequency stability issue has become more prominent than ever before. This paper proposes a supplementary control strategy to improve the frequency stability of the renewable energy integrated power system, which estimates the unbalanced power of the system by detecting the rate of change of frequency in the center of system inertia (COI) as well as the equivalent inertia level of the system, and adjusts the referenced power of the converter to provide inertia support for ac grids. The proposed unbalanced power estimating method includes two parts:rate of change of COI frequency detection and system equivalent inertia calculation. Since the COI frequency curve passes through the zero points of the second derivative of the local measurement frequency curve, the COI frequency curve can be approximated by the piecewise linear curve connected by the second derivative zero points. The system equivalent inertia considering the effective inertia of the non-synchronized components in the system can be obtained by counting the synchronous inertia of the system, change of active power of generators, and the total unbalanced power. Subsequently, an additional control method is proposed to compensate for unbalanced power based on the proportion of the capacities of renewable energies. The referenced power value of the renewable energy station will be quickly adjusted to suppress system frequency fluctuations when a frequency event occurs. PSCAD/EMTDC simulation verifies the effectiveness of the proposed additional control strategy.

Abstract:The power quality of the middle and low voltage distribution network will deteriorate due to the extension of power supply radius in the sparse areas. To deal with this problem, a direct voltage control strategy based on power electronic voltage regulator is proposed in this paper. The phase-locked loop of delayed signal cancellation and proportional-integral-resonant regulator are employed in this control strategy. And this control strategy quickly improves the power quality for the low and imbalanced voltage at the end of the line, which can dynamically and continuously compensate the line voltage. On this basis, this paper further deduces and verifies the mathematical relationship between the capacity of power electronic voltage regulator and the power supply radius, which provides a theoretical basis for the configuration of device in engineering. Finally, combined with the actual operation condition in the sparse area, a 10-kV power electronic voltage regulator model is developed in Matlab/Simulink. The results demonstrate the effectiveness of the proposed direct voltage control strategy and the accuracy of the mathematical relationship between the device capacity and the power supply radius.

Abstract:Energy storage unit is one of the key factorswhichcan ensure the reliable operation of DC microgrids. Traditional bi-directional Buck-Boost convertershave no advantages in voltage gain regulation and the correspondingcost, so a new design scheme is required to make a trade-off between the regulation capability and cost. First, for the energy storage system based on cascaded Buck-Boostconverter, this paper proposesa system-level design scheme whichusing cascaded Buck-Boostconverter as the sub module. Then, the voltage gain regulation of the cascaded Buck-Boostconverter in Buck and Boost mode is investigated by analyzing the working mode, and the modulation strategy is proposedfor the cascaded Buck-Boostconverter. At the same time, with the consideration of the operation mode of DC microgrid, the overall operation strategiesof energy storage system arefurther proposed to enable the storage to adoptthe appropriate control strategy to securethe reliable operation of microgrid under different working conditions. Finally, the effectiveness of the designed energy storage system and the control strategy areverified by several simulations.

Abstract:With the continuous expansion of the scale of the HVDC transmission system, the commutation failure in the converter station has an increasing impact on the safe and stable operation of the DC transmission project. This paper proposes the concept of an energy storage virtual synchronous machine, completes the construction of the model, and verifies that it has strong support for the commutation voltage drop of the HVDC system. Then,makingfull use of the reactive power compensation characteristics of the energy storage virtual synchronous machine.andthemulti-point deployment method using energy storage virtual synchronous machine is proposed to cope with multi-infeed DC commutation failure. The method firstly starts with the electrical distance between each node and the converter station to determine the area to be compensated.Then, calculates the average value of the non-fault point voltage response rate of the nodes in the compensation area is calculated.An indicator is used to determine the best The energy storage virtual synchronous machine installation site; finally, the simulation is performed in PSCAD to obtain the suppression effect of the single energy storage virtual synchronous machine access on the commutation failure.By comparing the actual grid operating data, it is verified that the proposedmethod couldeffectively exert the storage It can virtualize the aggregation effect of synchronous machines, and better suppress the failure of commutation.

Abstract:Aiming at the shortcomings of the existing weak link identification methods in the distribution network, a method for identifying weak links of the power grid based on off-grid load capacity was proposed, which considered the effect of the magnitude and duration of voltage sag on sensitive equipment. First, the magnitude and duration were divided into multiple intervals. Then, the analytical method was used to calculate the probability of the node voltage magnitude in each interval when the line failed; the probability density function of the duration distribution was fitted to calculate the probability of the voltage sag duration in each interval. From this, the probability of the magnitude and duration of node voltage sag in each interval was obtained when the line failed; that was the occurrence probability of voltage sag. Finally, based on the occurrence probability of voltage sag and the failure probability of sensitive equipment in each interval, the failure probability of sensitive equipment caused by line failure and the total off-grid load capacity of the power grid were calculated, and the off-grid load capacity was used as an indicator for identifying weak links of the power grid. Taking the IEEE-39 node system as an example for verification analysis and comparing it with other methods, the results showed the effectiveness of the proposed method.

Abstract:The admittance amplitude of inter-harmonic sources to ground is very small, so traditional parallel resonance analysis generally ignores the admittance of inter-harmonic sources to ground. However, if the admittance of inter-harmonic sources to ground has a greater influence on the parallel resonance to a high degree, ignoring the admittance of inter-harmonic sources to ground couldseriously reduce the accuracy of the parallel resonance analysis results.In order to prove the necessity of the parallel resonance analysis to include the admittance of inter-harmonic sources to ground, this paper establishes a parallel resonance test system based on the IEEE-33 nodes distribution network model, and carries out the research on the influence of admittance of inter-harmonic sources to ground on the parallel resonance of distribution network.Based on the modal analysis method, it is found that the admittance of inter-harmonic sources to ground at a specific node can significantly affect the parallel resonance. Through sensitivity analysis, it is found that the admittance imaginarypart of inter-harmonic sources to ground at a specific node has a greater influence on the high degree to the parallel resonance, which revealsthe reason why the admittance of inter-harmonic sources to ground can obviously affect the parallel resonance, and finally validatesthe necessity of including the admittance of inter-harmonic sources to ground in the parallel resonance analysis of distribution network.

Abstract:The access of large-scale distributed generators will impact the reliability of the distribution networks,which might be out of range by the traditional fault diagnosis methods. In the distribution networks with inverter interface distributed generator (IIDG), the fault current will change significantly due to the fast response of controllers.Therefore, in order to improve the comprehensive reliability, this paper extends the traditional fault analysis method, so that the root mean square (RMS) of fault current from theIIDG and the grid detection current can be calculated accurately forfault analysis. Through the simulation inthe IEEE standard distribution networks, the accuracy of the proposed methodunder different fault conditions is proved. This method can be applied for improving the stability, the reliability of distribution network operations, and the automation level of distribution networks.

Abstract:When single-phase grounding fault occurs in resonant grounded system in different fault conditions, the fault signals are very weak, which makes it difficult to detect the fault. According to the differences in characteristics of transient zero sequence current of short-time window time-frequency, the transient characteristics of the zero sequence current of single-phase earth fault is utilized and analyzed in this paper by S transform, where the zero-sequence current amplitude time-frequency matrix can be constructed based on these differences in characteristics. On the basis of multiple frequency information and local characteristics of time-frequency, a new method of fault line selection based on S-transform time-frequency characteristics is proposed in this paper. This method can be applied in the scenarios with the lack of information coverage in a single feature band and the inconsistent band characteristics of each feeder. Combined with the similarity assessment of image processing, the single-phase ground fault line selection for a resonant grounding system of a distribution network can be achieved by comprehensive correlation coefficients. The simulation results show that the new method will be less affected by fault initial angle, fault resistance, fault location and network structure. It can effectively distinguish different fault grounding types, and has obvious fault boundary, high reliability, strong anti-interference ability, and more extensive applicability.

Abstract:When a high-resistance ground fault occurs in the distribution network, the traditional route selection method is not sufficiently reliable.The difference of transient zero-sequence current under the condition of high resistance grounding while between the normal operated and fault lines is analyzed.The major difference is that the slopes of the corresponding trends of those two types of current are opposite.Therefore,a fault line selection method based on the slope of transient zero-sequence current envelope curve fitting is proposed.Firstly,the envelope curve of the transient zero-sequence current is obtained by the Newton interpolation algorithm,and then the fitting slope of each curve is calculated by the variable forgetting factor recursive least square method,and the resulting positive and negative characteristics of the slope values fitted by the envelope curves of the operating and the fault line can be utilized to construct the proposed fault line selection criterion.A large number of simulation results show that the route selection method proposed in this paper is suitable for various fault conditions.

Abstract:Asmost of the traditional measurement methods for the ground parameters of distribution network are mainly focus on the accurate measurement of the grounding capacitance, the grounding leakage resistance measurement is not accurate. The influence of the harmonic elimination resistance and the internal impedance of the voltage transformer is impossible to be eliminated during the measurement of the ground parameters. The issues mentioned above may result in a large error in the grounding leakage resistance measuring result.Furthermore, traditional measurement methods cannot be widely applied to different system grounding methods, and practical application is relatively inconvenient. To this end, this paper proposes a method for measuring the grounding leakage resistance of distribution network based on zero-sequence voltage regulation. In the proposed method, a small zero sequence voltage is obtained byselecting the appropriate shunting tapon a special Y/△-connected grounding transformer with shuntingtaps in the distribution network to ground.The corresponding zero sequence current of the system is measured.The grounding leakage resistance of the system can be calculated through the obtainedvoltage and current values. The PSCAD/EMTDC simulation software is used to verify and analyze the proposed grounding leakage resistance measurement method. The simulation resultsshow thatthe calculation method is applicable to different system connection mode with small measuring error,which indicates that theproposed method has the advance of high measurement accuracy, wide applicability, safety, economy and convenient use.

Abstract:In recent years, distribution network investment of county-level power supply companies continues to increase. There is a lack of a scientific and reasonable distribution network investment benefit evaluation system. This paper firstly constructs an investment evaluation index system for two-layer distribution network from the aspects of equipment level, power supply capacity, line loss reduction and power consumption increase. Secondly, the weight of each evaluation index is calculated by using analytic hierarchy process (AHP) and entropy method. Thirdly, the correlation of every evaluation index data is reduced by principal component analysis (PCA). Finally, the investment benefits of the distribution network of each evaluation object are ranked on the basis of TOPSIS. This method can be a reference for the superior management unit to evaluate the overall investment benefit in distribution network of county-level power supply company scientifically and reasonably, and then effectively guide the investment plan of distribution network in the next year.

Abstract:The ice galloping of overhead conductors is an essential factor leading to line trips, which seriously threatens the safety and stability of power system operation. How to calculate the tripping probability of the ice galloping of overhead conductors scientifically and rationally according to meteorological information has become an urgent problem to be solved. To calculate the short-circuit tripping probability of transmission line caused by galloping under the freezing weather, the information of wind speed, frozen rainfall, temperature, and humidity in the freezing weather area were first collected. Weibull distribution was used to fit the probability density distribution function of the wind speed and calculate the icing thickness of the conductor. Secondly, based on Newton's method, the single-degree-of-freedom galloping model of iced conductors was built. The Ritz-Galerkinn method was used to obtain the analytical expression of amplitude. The probability distribution function of the over-limit of galloping amplitude was obtained by combining the probability distribution of wind speed and the icing thickness. Then, the tripping probability is obtained by analyzing the phase relation of the three-phase conductor during the non-synchronous galloping. Finally, the Monte Carlo method is used to simulate the process of galloping tripping of an iced conductor, and the statistical value of galloping over-limit tripping probability is obtained. The results of an example show that the method can accurately calculate the probability of galloping tripping from the meteorological information obtained from the weather forecast.

Abstract:Through derivation and analysis on mathematical model of the temperature rise process of fuse melt under 8/20 μs lightning current, it is considered that the thermal conductivity of melt material, the normal temperature resistivity, the ambient temperature and the abnormal fracture of melt may affect the temperature rise process of fuse melt and then affect its working performance. On the basis of reasonably simplifying the melt structure of a fuse and putting forward relevant assumptions according to the actual situation, the melt thermoelectric coupling finite element model is established by using ANSYS, and the temperature rise of normal melt and melt affected by the above four factors under different lightning current amplitudes is simulated. The characteristic curves of lightning current amplitude-pre arc time of fuse are obtained. It is shown that these four factors will affect the melt temperature rise speed under the action of lightning current, and then affect the melt temperature rise process and the fuse pre arc time, which may cause the fuse to melt and reduce the working performance. Finally, through the comparison of simulation results, four measures to ensure the safe and normal operation of fuse are put forward.

Abstract:The accuracy of the intelligent transformer fault diagnosis method based on the DGA data is easily affected by the input characteristics, and the parametersof the extreme learning machine model is difficult to select. Thus, a transformer fault diagnosis method based on the neighborhood rough set and the adaptive mutation particle swarm extreme learning machine algorithm is proposed. Firstly, the initial feature set of transformer faults is established based on the various DGA fault diagnosis standards, and the key feature indicators with higherimportance according to the neighborhood rough set analysis.Secondly, when optimizing the parameters of the extreme learning machine on the basis ofthe particle swarm algorithm, it is easy to be premature and fall into the local maximum. Hence, an improved particle swarm optimization algorithm with premature self-check mutation mechanism is proposed.Finally, through a case study, the proposed methodis compared with the IEC three-ratio method and the different combinations of extreme learning machines,which verifies that the better diagnosis accuracy of the proposed method.

Abstract:Association rule mining methods are commonly utilized to analyze the dissolved gas which is applied to diagnose the power transformer fault events. For the purpose of improving the performance, this paper proposes a diagnosis method for power transformer fault events based on the enhanced association rule mining algorithm. Firstly, the conditional significance measurements which can be adapted for different input features are established. Thus the rarely distributed but risky data can be incorporated in analysis, and all the potential circumstances in reality can be considered. Next, the corresponding risk weights of input data are generated through their probability of causing a fault rather than their statistical distribution. Therefore, the impact of each input will be measured more precisely. Finally, Relim algorithm is applied to raise the efficiency of mining. The experimentalstudy shows that the proposed method is more pinpoint, realizable and efficient compared with the methods with the fixed significance measurements, the conventional technique to calculatethe risk weight, and Apriori algorithm.

Abstract:In order to solve the problem that serious insulation fault caused by free pulsation of spherical metal particles in GIL, an experimental platform proportional shrunken according to GIL device is set up on the basis of analyzing the force of metal particles. The movement locus of metal particle and jumping field are filmed and recorded. The generality of the experimental results is guaranteed through multiple repetitive experiments. The results indicate that the particle jumping field is determined by the radius of the particles while the material is fixed. The gas pressure and the voltage polarity almost have no effect to the jumping field. The jumping field intensity decreases gradually with the increase of the quantity of neighboring particles. The pseudo resonance phenomena and firefly phenomena may appear when spherical particle moves in DC GIL. The probability of firefly phenomena increases with the increasing particle radius. The jump rate of the particles near the insulator is faster than that of the particles in the middle of the high voltage conductor. Multiple particles will cause the time-divided jumping phenomena and the movement locus is basically similar to the single particle.

Abstract:The power supply maintenance of sensors will hinder the application and development of the IoT (internet of things) system in substations. To handle it, this paper proposes a new power supply method for the IoT system in substations based on the wireless transmission to realize itsself-sustaining operations. Firstly, the energy acquisition and distribution model is established, the signal transmission model is analyzed, and the CSMA protocol is used to transmit signals on the time-slot shared channel to communicate with the power supply nodes, which can effectively reduce the multi-node wireless power supply channel competition. Secondly, the evolution of sensor energy is analyzed, and two sensor energy supply schemes are designed. Among them, the sub-optimal scheme assigns power to each node fixedly to achieve simpler implementation rather than performance.The other scheme will dynamically adjust the allocation, to provide the maximum power for each node, and get the best energy distribution ratio which can improve the wireless power supply efficiency of the system. Finally, a 10-node simulation model is established to verify the effectiveness of the proposed method. The results show that the method proposed in this paper can realize the self-sustaining of the substation IoT system.

Abstract:The power switch is a basic component of the power system. The switch status during system operation and maintenance often needs to be manually confirmed for multiple times. Under the background, a new method for recognizing the state of the knife switch is proposed. Firstly, the input 3D knife gate image is converted into color point cloud data, and the scene features are extracted from the color point cloud data. Then, the existing direction histogram color feature description algorithm is employed to construct the recognition feature of descriptor based on the local texture and shape information. With the given extracted feature descriptors, a two-stage matching process is performed to find the correspondence between the scene and the color point cloud model of the target. Secondly, the Hough voting algorithm is utilized to filter the matching errors in the corresponding set and estimate the initial three-dimensional posture of the knife gate. Finally, in the pose estimation stage, the random sample consistency and hypothesis verification algorithms are used to improve the initial pose and filter out bad estimation results with incorrect assumptions. The experimental results show that the method can successfully identify the switch parts in complex power scenes, and can accurately estimate the three-dimensional posture information of the target.

Abstract:The infrared thermal imaging detection method has unique advantages inthe diagnosis of low/zero-valued porcelain insulators. However, anEHV/UHV porcelain insulator string is generally too long (even 10 meters or above) to be entirely displayed in a single infrared imageshotbyan industrial handheld/airborne thermal camera, which causes serious difficulties to the intelligent diagnosis of deterioration based on the whole string temperature characteristics. To solve this problem, this article proposes a double-segmenttemperature curve splicing method based on weighted data fusion. This methodcan solve the problems of target missing byapplying general infrared image splicingtechnology, and can obtainhigher fitting accuracy compared with curve splicing methods such as rounding and midpoint splicing. The basic algorithm and process of the proposed curve splicing method are illustrated through an example ofa 1 000 kV insulator string.A comparative study of various curve splicing methods is carried out by taking a 500 kV insulator string into account.Therefore,the effectiveness and feasibility of the proposed method are verified.

Abstract:As an important component of overhead transmission lines, transmission wires may cause major power accidents if they are found to be defective during the inspection process. The identification of wire defects in high-pixel UAV inspection images requires a large amount of calculation and the target area of defects is small. If real-time high-precision identification is realized in the UAV inspection process, the inspection efficiency can be greatly accelerated. This paper proposes a method to identify wire defects by using the on-board computer of UAV to process high-resolution wire images collected by high-definition cameras in real time. The method firstly uses semantic information patching to sub-sample the wire image, and then uses the segmentation network to obtain the low-pixel wire segmentation areas and mesh them. Multiple wire areas are cropped out and mapped back to the high-pixel original image at a down-sampling ratio. Then a number of high-resolution wire areas are cut out and enter the yolov3 network in batch for wire defect recognition. Finally the defect recognition target area is produced according to the input high-precision attention area in the relative position of the original image. The experimental results show that the identification method proposed in this paper can realize the real-time identification of high frame rate defects in the high-resolution wire images collected by the camera in the process of UAV patrolling, which provides a new idea for the intelligent patrolling of UAV.